research-report

GitHub

将深度调研的JSON结果汇总为Markdown报告。通过定位目录、扫描字段、生成并执行Python脚本,兼容多种JSON结构,处理多语言映射与不确定值过滤,最终输出包含目录和详细内容的标准化报告。

skills/research-zh/research-report/SKILL.md Weizhena/Deep-Research-skills

Trigger Scenarios

用户输入/research-report指令 需要将deep调研结果转换为结构化Markdown文档

Install

npx skills add Weizhena/Deep-Research-skills --skill research-report -g -y
More Options

Non-standard path

npx skills add https://github.com/Weizhena/Deep-Research-skills/tree/master/skills/research-zh/research-report -g -y

Use without installing

npx skills use Weizhena/Deep-Research-skills@research-report

指定 Agent (Claude Code)

npx skills add Weizhena/Deep-Research-skills --skill research-report -a claude-code -g -y

安装 repo 全部 skill

npx skills add Weizhena/Deep-Research-skills --all -g -y

预览 repo 内 skill

npx skills add Weizhena/Deep-Research-skills --list

SKILL.md

Frontmatter
{
    "name": "research-report",
    "description": "将deep调研结果汇总为markdown报告,覆盖所有字段,跳过不确定值。",
    "allowed-tools": "Read, Write, Glob, Bash, AskUserQuestion",
    "user-invocable": true
}

Research Report - 汇总报告

触发方式

/research-report

执行流程

Step 1: 定位结果目录

在当前工作目录查找 */outline.yaml,读取topic和output_dir配置。

Step 2: 扫描可选摘要字段

读取所有JSON结果,提取适合在目录中显示的字段(数值型、简短指标),例如:

  • github_stars
  • google_scholar_cites
  • swe_bench_score
  • user_scale
  • valuation
  • release_date

使用AskUserQuestion询问用户:

  • 目录中除了item名称外,还需要显示哪些字段?
  • 提供动态选项列表(基于实际JSON中存在的字段)

Step 3: 生成Python转换脚本

{topic}/ 目录下生成 generate_report.py,脚本要求:

  • 读取output_dir下所有JSON
  • 读取fields.yaml获取字段结构
  • 覆盖每个JSON的所有字段值
  • 跳过值包含[不确定]的字段
  • 跳过uncertain数组中列出的字段
  • 生成markdown报告格式:目录(带锚点跳转+用户选择的摘要字段)+ 详细内容(按字段分类)
  • 保存到 {topic}/report.md

目录格式要求

  • 必须包含每一个item
  • 每个item显示:序号、名称(锚点链接)、用户选择的摘要字段
  • 示例:1. [GitHub Copilot](#github-copilot) - Stars: 10k | Score: 85%

脚本技术要点(必须遵循)

1. JSON结构兼容 支持两种JSON结构:

  • 扁平结构:字段直接在顶层 {"name": "xxx", "release_date": "xxx"}
  • 嵌套结构:字段在category子dict中 {"basic_info": {"name": "xxx"}, "technical_features": {...}}

字段查找顺序:顶层 -> category映射key -> 遍历所有嵌套dict

2. Category多语言映射 fields.yaml的category名与JSON的key可能是任意组合(中中、中英、英中、英英)。必须建立双向映射:

CATEGORY_MAPPING = {
    "基本信息": ["basic_info", "基本信息"],
    "技术特性": ["technical_features", "technical_characteristics", "技术特性"],
    "性能指标": ["performance_metrics", "performance", "性能指标"],
    "里程碑意义": ["milestone_significance", "milestones", "里程碑意义"],
    "商业信息": ["business_info", "commercial_info", "商业信息"],
    "竞争与生态": ["competition_ecosystem", "competition", "竞争与生态"],
    "历史沿革": ["history", "历史沿革"],
    "市场定位": ["market_positioning", "market", "市场定位"],
}

3. 复杂值格式化

  • list of dicts(如key_events, funding_history):每个dict格式化为一行,用|分隔kv
  • 普通list:短列表用逗号连接,长列表换行显示
  • 嵌套dict:递归格式化,用分号或换行显示
  • 长文本字符串(超过100字符):添加换行符<br>或使用blockquote格式,提高可读性

4. 额外字段收集 收集JSON中有但fields.yaml中没定义的字段,放入"其他信息"分类。注意过滤:

  • 内部字段:_source_file, uncertain
  • 嵌套结构顶级key:basic_info, technical_features
  • uncertain数组:需要逐行显示每个字段名,不要压缩成一行

5. 不确定值跳过 跳过条件:

  • 字段值包含[不确定]字符串
  • 字段名在uncertain数组中
  • 字段值为None或空字符串

Step 4: 执行脚本

运行 python {topic}/generate_report.py

输出

  • {topic}/generate_report.py - 转换脚本
  • {topic}/report.md - 汇总报告

Version History

  • e5479f8 Current 2026-07-24 22:31

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skills/research-codex-en/research-report/SKILL.md
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skills/research-zh/research-deep/SKILL.md

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